Learning path to Data Science

Many people asked me what is the path and what they should learn to become Data Scientist or to understand Data Science (DS). Here is the learning I did and some meaningful on this subject.

I will update this post from time to time. Don’t hesitate to let me know about your own course or post in comments.


Machine Learning from Coursera
This course in Coursera has been followed by more than 2 million people, yes, 2 millions ! It is very nicely done and make Data Science easy by the way Andrew Ng teaches it.
Usually when I talked about this course, people already knowledgeable in DS already knows about it.
This course is all about theories behind Machine Learning (ML) and there are some extensive hands on on Matlab/Octave. Be prepare to learn or use about math (matrices, derivatives, functions) and some coding too.
Link : https://www.coursera.org/learn/machine-learning/home/welcome

This site is managed by IBM and there are a lot of interesting courses. Moreover you can get $1200 worth of credit in the IBM Cloud to train and test and your learning.
Data Analysis with Python : Learn how to analyze data using Python. This course will take you from the basics of Python to exploring many different types of data. You will learn how to prepare data for analysis, perform simple statistical analyses, create meaningful data visualizations, predict future trends from data, and more!
Machine Learning with Python : Learn about how to use Python Libraries. This is a good follow up to have Python hands on after the Machine Learning Course from Coursera.


Medium.com is a great source of DS posts

10 Machine Learning Methods that Every Data Scientist Should Know : A good list of all subjects in DS

Leave a Comment

NOTE - You can use these HTML tags and attributes:
<a href="" title=""> <abbr title=""> <acronym title=""> <b> <blockquote cite=""> <cite> <code> <del datetime=""> <em> <i> <q cite=""> <s> <strike> <strong>

This site uses Akismet to reduce spam. Learn how your comment data is processed.